Vision Mamba, a state space model architecture, is gaining attention for its efficiency in visual representation learning. It is 2.8x faster than DeiT and more suitable for high-resolution tasks, saving 86.8% GPU memory during batch inference. Researchers are increasingly interested in Mamba, and it is being integrated into various platforms, including LocalAI and MLX implementation.
Cool new repo - a complete Mamba implementation in MLX! Includes inference and training. Mamba is a state space model so fixed memory even for long generations. Code: https://t.co/RlB2lsimwh Generating with the 2.8B model (in 32-bit precision) on an M2 Ultra: https://t.co/kmSenptYuq https://t.co/i8ptL0HLGz
Happy to release an MLX implementation of Mamba π, now part of https://t.co/KVFPYoTN80 Run inference of pretrained models and train models right on your Mac ! https://t.co/opw5iFpcSa
Beyond Transformers: Structured State Space Sequence Models Mamba is getting more popular recently, it's time to learn about state space models. https://t.co/32QGwPvcBJ https://t.co/Xnj79k5AeV
Vision Mamba Efficient Visual Representation Learning with Bidirectional State Space Model https://t.co/8XQEtX9xOK https://t.co/WgXrSUuqTy
Weekend hack time: adding mamba π to @LocalAI_API ! Mamba is a new state space model architecture showing promising performance: https://t.co/9v11QwSAyQ https://t.co/qvgSDS56KB Merged, and soon in LocalAI v2.6.0 https://t.co/jJPh7ePNzp !
The most promising challenger to transformers: the state space model, which is getting a lot of buzz from researchers. https://t.co/ExJCeoBH1u AI Agenda by @steph_palazzolo
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model abs: https://t.co/GxY6Zn2k5m Proposes Vision Mamba (Vim), which uses a bidirectional Mamba network, 2.8x faster than DeiT, more suitable for high-resolution tasks. https://t.co/Ed39EsxatY
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model 2.8x faster than DeiT and saves 86.8% GPU memory when performing batch inference to extract features on high-res images repo: https://t.co/VK8bEts8bx abs: https://t.co/peRRPHVc2Y https://t.co/CYpEVctSIB